“The Lifeblood of College Sports”: The NCAA’s Dominant Institutional Logic and the Byproducts of an (Over)emphasis on Recruiting

In big-time college football, successful recruiting is the foundation on which winning programs stand. Power-5 football and men’s basketball operate under a dominant institutional logic that values generating revenue above all else. Winning generates revenue and, accordingly, Power-5 stakeholders are often engulfed in their unique athletic roles. The system propagates adherence to a singular focus that emphasizes winning and revenue generation. This dominant institutional logic governing big-time college football has been dubbed jock capitalism (Southall & Nagel, 2009). While prominent theorists have analyzed college sports through an institutional logic perspective, a systematic examination of the Power-5 football recruiting process has not been conducted to this point. The three parts of this dissertation aimed to examine components of the college football recruiting process through the primary framework of Power-5 football’s dominant institutional logic. Findings reveal that athletic role engulfment and racially tasked disparate roles have been institutionalized within Southeastern Conference (SEC) football; proliferated by institutional actors (e.g. recruiters and coaches) and adhered to by recruits and players. In the SEC, the emphasis placed on winning football games directly reflects an institutional jock capitalism logic

Chasing Stars: Racial Tasking of Recruiting Responsibilities among Power-5 Football Coaches

During the 2022 National Collegiate Athletic Association (NCAA) college football season, eight of the 65 Power-5 head coaches were Black. The racial composition of assistant coaches, however, was nearly 50% Black and 50% White. While the head coach of a Power-5 football team serves as the leader of the program, the 10 assistant coaches permitted by the NCAA oversee a variety of critical roles; the most valuable of which is recruiting. This study extends previous work by examining the racial composition of Power-5 football coaching staffs and recruiting responsibilities through the lens of racial tasking. An analysis of Power-5 football recruiting classes from 2019 and 2020 illustrates that assistant coaches are tasked with recruiting recruits racially similar to themselves 58% of the time. Furthermore, Black assistant coaches are disproportionately tasked with recruiting Black recruits and higher rated recruits (i.e., five- and four-star) compared to their White counterparts. We contend such racialized responsibilities and expectations may affect opportunities for advancement among Black assistant coaches

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

2020 roadmap on solid-state batteries

Li-ion batteries have revolutionized the portable electronics industry and empowered the electric vehicle (EV) revolution. Unfortunately, traditional Li-ion chemistry is approaching its physicochemical limit. The demand for higher density (longer range), high power (fast charging), and safer EVs has recently created a resurgence of interest in solid state batteries (SSB). Historically, research has focused on improving the ionic conductivity of solid electrolytes, yet ceramic solids now deliver sufficient ionic conductivity. The barriers lie within the interfaces between the electrolyte and the two electrodes, in the mechanical properties throughout the device, and in processing scalability. In 2017 the Faraday Institution, the UK's independent institute for electrochemical energy storage research, launched the SOLBAT (solid-state lithium metal anode battery) project, aimed at understanding the fundamental science underpinning the problems of SSBs, and recognising that the paucity of such understanding is the major barrier to progress. The purpose of this Roadmap is to present an overview of the fundamental challenges impeding the development of SSBs, the advances in science and technology necessary to understand the underlying science, and the multidisciplinary approach being taken by SOLBAT researchers in facing these challenges. It is our hope that this Roadmap will guide academia, industry, and funding agencies towards the further development of these batteries in the future

Open Source Dataset and Deep Learning Models for Online Digit Gesture Recognition on Touchscreens

Irish Machine Vision and Image Processing Conference (IMVIP), Maynooth University, Ireland, 30 August- 1 September 2017This paper presents an evaluation of deep neural networks for recognition of digits entered by users on a smartphone touchscreen. A new large dataset of Arabic numerals was collected for training and evaluation of the network. The dataset consists of spatial and temporal touch data recorded for 80 digits entered by 260 users. Two neural network models were investigated. The first model was a 2D convolutional neural (ConvNet) network applied to bitmaps of the glpyhs created by interpolation of the sensed screen touches and its topology is similar to that of previously published models for offline handwriting recognition from scanned images. The second model used a 1D ConvNet architecture but was applied to the sequence of polar vectors connecting the touch points. The models were found to provide accuracies of 98.50% and 95.86%, respectively. The second model was much simpler, providing a reduction in the number of parameters from 1,663,370 to 287,690. The dataset has been made available to the community as an open source resource